ArticleNucleic acids research2008
Uncovering signal transduction networks from high-throughput data by integer linear programming.
Article in Nucleic acids research, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.
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Who cites it
55 citing papers in PubMed.
- Spatial proximity and gene function: a new dimension in prokaryotic gene association network analysis with 3D-GeneNet.Briefings in bioinformatics · 2024Article
- A multi-source molecular network representation model for protein-protein interactions prediction.Scientific reports · 2024Article
- PSF toolkit: an R package for pathway curation and topology-aware analysis.Frontiers in genetics · 2023Article
- Phosprof: pathway analysis database of drug response based on phosphorylation activity measurements.Database : the journal of biological databases and curation · 2022Article
- De novo identification of maximally deregulated subnetworks based on multi-omics data with DeRegNet.BMC bioinformatics · 2022Article
- Network approach to understand biological systems: From single to multilayer networks.Journal of biosciences · 2022Article
- Identifying intracellular signaling modules and exploring pathways associated with breast cancer recurrence.Scientific reports · 2021Article
- Conceptual Evolution of Cell Signaling.International journal of molecular sciences · 2019Review
- Stems cells, big data and compendium-based analyses for identifying cell types, signalling pathways and gene regulatory networks.Biophysical reviews · 2019Review
- pathfindR: An R Package for Comprehensive Identification of Enriched Pathways in Omics Data Through Active Subnetworks.Frontiers in genetics · 2019Article
- Identification of active signaling pathways by integrating gene expression and protein interaction data.BMC systems biology · 2018Article
- The node-weighted Steiner tree approach to identify elements of cancer-related signaling pathways.BMC bioinformatics · 2017Article
- Protein-Protein Interactions Prediction Using a Novel Local Conjoint Triad Descriptor of Amino Acid Sequences.International journal of molecular sciences · 2017Article
- Bayesian network model for identification of pathways by integrating protein interaction with genetic interaction data.BMC systems biology · 2017Article
- Signalling pathway impact analysis based on the strength of interaction between genes.IET systems biology · 2016Article
- Predicting hot spots in protein interfaces based on protrusion index, pseudo hydrophobicity and electron-ion interaction pseudopotential features.Oncotarget · 2016Article
- Pathogenic Network Analysis Predicts Candidate Genes for Cervical Cancer.Computational and mathematical methods in medicine · 2016Article
- Identify asthma genes across three phases based on protein-protein interaction network.IET systems biology · 2015Article
- Mutated genes and driver pathways involved in myelodysplastic syndromes—a transcriptome sequencing based approach.Molecular bioSystems · 2015Article
- Pathway crosstalk analysis of microarray gene expression profile in human hepatocellular carcinoma.Pathology oncology research : POR · 2015Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Signal transduction is an important process that transmits signals from the outside of a cell to the inside to mediate sophisticated biological responses. Effective computational models to unravel such a process by taking advantage of high-throughput genomic and proteomic data are needed to understand the essential mechanisms underlying the signaling pathways. In this article, we propose a novel method for uncovering signal transduction networks (STNs) by integrating protein interaction with gene expression data. Specifically, we formulate STN identification problem as an integer linear programming (ILP) model, which can be actually solved by a relaxed linear programming algorithm and is flexible for handling various prior information without any restriction on the network structures. The numerical results on yeast MAPK signaling pathways demonstrate that the proposed ILP model is able to uncover STNs or pathways in an efficient and accurate manner. In particular, the prediction results are found to be in high agreement with current biological knowledge and available information in literature. In addition, the proposed model is simple to be interpreted and easy to be implemented even for a large-scale system.
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